def _process_pathways(self, limit=None):
"""
This method adds the KEGG pathway IDs.
These are the canonical pathways as defined in KEGG.
We also encode the graphical depiction
which maps 1:1 with the identifier.
Triples created:
<pathway_id> is a GO:signal_transduction
<pathway_id> rdfs:label <pathway_name>
<gene_id> RO:involved_in <pathway_id>
:param limit:
:return:
"""
logger.info("Processing pathways")
if self.testMode:
g = self.testgraph
else:
g = self.graph
model = Model(g)
line_counter = 0
path = Pathway(g)
raw = '/'.join((self.rawdir, self.files['pathway']['file']))
with open(raw, 'r', encoding="iso-8859-1") as csvfile:
filereader = csv.reader(csvfile, delimiter='\t', quotechar='\"')
for row in filereader:
line_counter += 1
(pathway_id, pathway_name) = row
if self.testMode and \
pathway_id not in self.test_ids['pathway']:
continue
pathway_id = 'KEGG-'+pathway_id.strip()
path.addPathway(pathway_id, pathway_name)
# we know that the pathway images from kegg map 1:1 here.
# so add those
image_filename = re.sub(r'KEGG-path:', '', pathway_id) + '.png'
image_url = \
'http://www.genome.jp/kegg/pathway/map/'+image_filename
model.addDepiction(pathway_id, image_url)
if not self.testMode and \
limit is not None and line_counter > limit:
break
logger.info("Done with pathways")
return
def _process_pathways(self, limit=None):
"""
This method adds the KEGG pathway IDs.
These are the canonical pathways as defined in KEGG.
We also encode the graphical depiction
which maps 1:1 with the identifier.
Triples created:
<pathway_id> is a GO:signal_transduction
<pathway_id> rdfs:label <pathway_name>
<gene_id> RO:involved_in <pathway_id>
:param limit:
:return:
"""
LOG.info("Processing pathways")
if self.test_mode:
graph = self.testgraph
else:
graph = self.graph
model = Model(graph)
path = Pathway(graph)
raw = '/'.join((self.rawdir, self.files['pathway']['file']))
with open(raw, 'r', encoding="iso-8859-1") as csvfile:
reader = csv.reader(csvfile, delimiter='\t', quotechar='\"')
for row in reader:
(pathway_id, pathway_name) = row
if self.test_mode and pathway_id not in self.test_ids['pathway']:
continue
pathway_id = 'KEGG-'+pathway_id.strip()
path.addPathway(pathway_id, pathway_name)
# we know that the pathway images from kegg map 1:1 here.
# so add those
image_filename = re.sub(r'KEGG-path:', '', pathway_id) + '.png'
image_url = 'http://www.genome.jp/kegg/pathway/map/'+image_filename
model.addDepiction(pathway_id, image_url)
if not self.test_mode and limit is not None and reader.line_num > limit:
break
LOG.info("Done with pathways")
def _process_nlx_157874_1_view(self, raw, limit=None):
"""
This table contains the Elements of Morphology data .
Note that foaf:depiction is inverse of foaf:depicts relationship.
Since it is bad form to have two definitions,
we concatenate the two into one string.
Turtle:
<eom id> a owl:Class
rdf:label Literal(eom label)
oboInOwl:has_related_synonym Literal(synonym list)
IAO:definition Literal(objective_def. subjective def)
foaf:depiction Literal(small_image_url),
Literal(large_image_url)
foaf:page Literal(page_url)
rdfs:comment Literal(long commented text)
TEC_note: URL are not literals.
:param raw:
:param limit:
:return:
"""
src_key = 'tables'
model = Model(self.graph)
col = self.resources[src_key]['columns']
with open(raw, 'r') as rawread:
reader = csv.reader(rawread, delimiter='\t', quotechar='\"')
row = next(reader)
if not self.check_fileheader(col, row):
pass
for row in reader:
# head -1 dvp.pr_nlx_157874_1|tr '\t' '\n'|
# sed "s|\(.*\)|# \1 = row[col.index('\1')]|g"
morphology_term_id = row[col.index(
'morphology_term_id')].strip()
# morphology_term_num = row[col.index('morphology_term_num')]
morphology_term_label = row[col.index(
'morphology_term_label')].strip()
morphology_term_url = row[col.index(
'morphology_term_url')].strip()
# terminology_category_label = row[
# col.index('terminology_category_label')]
# terminology_category_url = row[col.index('terminology_category_url')]
# subcategory = row[col.index('subcategory')]
objective_definition = row[col.index(
'objective_definition')].strip()
subjective_definition = row[col.index(
'subjective_definition')].strip()
comments = row[col.index('comments')].strip()
synonyms = row[col.index('synonyms')].strip()
replaces = row[col.index('replaces')].strip()
small_figure_url = row[col.index('small_figure_url')].strip()
large_figure_url = row[col.index('large_figure_url')].strip()
# e_uid = row[col.index('e_uid')]
# v_uid = row[col.index('v_uid')]
# v_uuid = row[col.index('v_uuid')]
# v_lastmodified = row[col.index('v_lastmodified')]
# v_status = row[col.index('v_status')]
# v_lastmodified_epoch = row[col.index('v_lastmodified_epoch')]
# Add morphology term to graph as a class
# with label, type, and description.
model.addClassToGraph(morphology_term_id,
morphology_term_label)
# Assemble the description text
if subjective_definition != '' and not (re.match(
r'.+\.$', subjective_definition)):
# add a trailing period.
subjective_definition = subjective_definition + '.'
if objective_definition != '' and not (re.match(
r'.+\.$', objective_definition)):
# add a trailing period.
objective_definition = objective_definition + '.'
definition = ' '.join(
(objective_definition, subjective_definition))
model.addDefinition(morphology_term_id, definition)
# <term id> FOAF:depicted_by literal url
# <url> type foaf:depiction
# do we want both images?
# morphology_term_id has depiction small_figure_url
if small_figure_url != '':
model.addDepiction(morphology_term_id, small_figure_url)
# morphology_term_id has depiction large_figure_url
if large_figure_url != '':
model.addDepiction(morphology_term_id, large_figure_url)
# morphology_term_id has comment comments
if comments != '':
model.addComment(morphology_term_id, comments)
for syn in synonyms.split(';'):
model.addSynonym(morphology_term_id, syn.strip(),
self.globaltt['has_exact_synonym'])
# morphology_term_id has_related_synonym replaces (; delimited)
if replaces not in ['', synonyms]:
for syn in replaces.split(';'):
model.addSynonym(morphology_term_id, syn.strip(),
self.globaltt['has_related_synonym'])
# <morphology_term_id> <foaf:page> morphology_term_url
if morphology_term_id is not None:
reference = Reference(self.graph, morphology_term_id,
self.globaltt['web page'])
# TEC 201905:
# Not so sure we need explicit <eom_uri> <webpage> <eom_url>.
# since <eom_uri> IS the <eom_url>.
reference.addPage(morphology_term_id, morphology_term_url)
if limit is not None and reader.line_num > limit:
break
def _process_nlx_157874_1_view(self, raw, limit=None):
"""
This table contains the Elements of Morphology data that has been
screen-scraped into DISCO.
Note that foaf:depiction is inverse of foaf:depicts relationship.
Since it is bad form to have two definitions,
we concatenate the two into one string.
Triples:
<eom id> a owl:Class
rdf:label Literal(eom label)
OIO:hasRelatedSynonym Literal(synonym list)
IAO:definition Literal(objective_def. subjective def)
foaf:depiction Literal(small_image_url),
Literal(large_image_url)
foaf:page Literal(page_url)
rdfs:comment Literal(long commented text)
:param raw:
:param limit:
:return:
"""
model = Model(self.graph)
line_counter = 0
with open(raw, 'r') as f1:
f1.readline() # read the header row; skip
filereader = csv.reader(f1, delimiter='\t', quotechar='\"')
for line in filereader:
line_counter += 1
(morphology_term_id, morphology_term_num,
morphology_term_label, morphology_term_url,
terminology_category_label, terminology_category_url,
subcategory, objective_definition, subjective_definition,
comments, synonyms, replaces, small_figure_url,
large_figure_url, e_uid, v_uid, v_uuid,
v_last_modified, v_status, v_lastmodified_epoch) = line
# note:
# e_uid v_uuid v_last_modified terminology_category_url
# subcategory v_uid morphology_term_num
# terminology_category_label hp_label notes
# are currently unused.
# Add morphology term to graph as a class
# with label, type, and description.
model.addClassToGraph(morphology_term_id,
morphology_term_label)
# Assemble the description text
if subjective_definition != '' and not (
re.match(r'.+\.$', subjective_definition)):
# add a trailing period.
subjective_definition = subjective_definition.strip() + '.'
if objective_definition != '' and not (
re.match(r'.+\.$', objective_definition)):
# add a trailing period.
objective_definition = objective_definition.strip() + '.'
definition = \
' '.join(
(objective_definition, subjective_definition)).strip()
model.addDefinition(morphology_term_id, definition)
# <term id> FOAF:depicted_by literal url
# <url> type foaf:depiction
# do we want both images?
# morphology_term_id has depiction small_figure_url
if small_figure_url != '':
model.addDepiction(morphology_term_id,
small_figure_url)
# morphology_term_id has depiction large_figure_url
if large_figure_url != '':
model.addDepiction(morphology_term_id,
large_figure_url)
# morphology_term_id has comment comments
if comments != '':
model.addComment(morphology_term_id,
comments.strip())
if synonyms != '':
for s in synonyms.split(';'):
model.addSynonym(
morphology_term_id, s.strip(),
model.annotation_properties['hasExactSynonym'])
# morphology_term_id hasRelatedSynonym replaces (; delimited)
if replaces != '' and replaces != synonyms:
for s in replaces.split(';'):
model.addSynonym(
morphology_term_id, s.strip(),
model.annotation_properties['hasRelatedSynonym'])
# morphology_term_id has page morphology_term_url
reference = Reference(self.graph)
reference.addPage(morphology_term_id, morphology_term_url)
if limit is not None and line_counter > limit:
break
return
def _process_nlx_157874_1_view(self, raw, limit=None):
"""
This table contains the Elements of Morphology data that has been
screen-scraped into DISCO.
Note that foaf:depiction is inverse of foaf:depicts relationship.
Since it is bad form to have two definitions,
we concatenate the two into one string.
Triples:
<eom id> a owl:Class
rdf:label Literal(eom label)
OIO:hasRelatedSynonym Literal(synonym list)
IAO:definition Literal(objective_def. subjective def)
foaf:depiction Literal(small_image_url),
Literal(large_image_url)
foaf:page Literal(page_url)
rdfs:comment Literal(long commented text)
:param raw:
:param limit:
:return:
"""
model = Model(self.graph)
line_counter = 0
with open(raw, 'r') as f1:
f1.readline() # read the header row; skip
filereader = csv.reader(f1, delimiter='\t', quotechar='\"')
for line in filereader:
line_counter += 1
(morphology_term_id, morphology_term_num,
morphology_term_label, morphology_term_url,
terminology_category_label, terminology_category_url,
subcategory, objective_definition, subjective_definition,
comments, synonyms, replaces, small_figure_url,
large_figure_url, e_uid, v_uid, v_uuid, v_last_modified,
v_status, v_lastmodified_epoch) = line
# note:
# e_uid v_uuid v_last_modified terminology_category_url
# subcategory v_uid morphology_term_num
# terminology_category_label hp_label notes
# are currently unused.
# Add morphology term to graph as a class
# with label, type, and description.
model.addClassToGraph(morphology_term_id,
morphology_term_label)
# Assemble the description text
if subjective_definition != '' and not (re.match(
r'.+\.$', subjective_definition)):
# add a trailing period.
subjective_definition = subjective_definition.strip() + '.'
if objective_definition != '' and not (re.match(
r'.+\.$', objective_definition)):
# add a trailing period.
objective_definition = objective_definition.strip() + '.'
definition = \
' '.join(
(objective_definition, subjective_definition)).strip()
model.addDefinition(morphology_term_id, definition)
# <term id> FOAF:depicted_by literal url
# <url> type foaf:depiction
# do we want both images?
# morphology_term_id has depiction small_figure_url
if small_figure_url != '':
model.addDepiction(morphology_term_id, small_figure_url)
# morphology_term_id has depiction large_figure_url
if large_figure_url != '':
model.addDepiction(morphology_term_id, large_figure_url)
# morphology_term_id has comment comments
if comments != '':
model.addComment(morphology_term_id, comments.strip())
if synonyms != '':
for s in synonyms.split(';'):
model.addSynonym(
morphology_term_id, s.strip(),
model.annotation_properties['hasExactSynonym'])
# morphology_term_id hasRelatedSynonym replaces (; delimited)
if replaces != '' and replaces != synonyms:
for s in replaces.split(';'):
model.addSynonym(
morphology_term_id, s.strip(),
model.annotation_properties['hasRelatedSynonym'])
# morphology_term_id has page morphology_term_url
reference = Reference(self.graph)
reference.addPage(morphology_term_id, morphology_term_url)
if limit is not None and line_counter > limit:
break
return
